Project Summary/Abstract The ability for an animal or human to perceive a subtle environmental stimulus is not a fixed parameter. Rather, perceptual thresholds fluctuate with changes in arousal, attention, and expectation. Similarly, individual neurons within the visual cortex exhibit variable responses when repeatedly presented the same stimulus, an observation widely thought to contribute to perceptual variability. However, injection of identical noisy currents evokes highly precise spike trains, indicating that these fluctuations are not due to a noisy spiking mechanism. Instead, it largely reflects moment-by-moment synaptic input from the cortical network. These network fluctuations are reflected in local field potentials (LFPs). Here, new computational methods have been used to show for the first time that spontaneous fluctuations are organized into traveling waves in awake, behaving primates. These methods enable tracking of traveling waves on a moment-by-moment basis, without trial averaging analyses. Spontaneous waves create periods of both elevated and suppressed spiking activity, and preliminary data indicate that they modulate stimulus-evoked spiking responses and perceptual sensitivity in a visual detection task. Thus, the assembled team is well positioned to understand the role of neocortical traveling waves in perception and propose three Aims. Aim 1: Test whether spontaneous activity in awake marmoset MT and V1 is organized into traveling waves. Utah arrays will be implanted in marmoset area MT and V1 to record spikes and LFPs while the monkey fixates a blank screen. Network fluctuations will be detected to test the hypothesis that spontaneous spiking activity generates traveling waves that can be detected in the LFP, and the phase of LFP fluctuations reflect periods of depolarization and hyperpolarization. Aim 2: Develop a spiking network model linking LFP waves, spiking activity and perception. A preliminary computational model has been developed that accounts for spike-LFP relationships observed in experimental data. Here, the model will be extended to quantitatively match properties of observed traveling waves, and then used to generate testable predictions about how the phase of LFP waves affects spiking probability, stimulus-evoked responses, and perceptual sensitivity (the latter by extending the model within an ideal observer framework). Aim 3: Determine the impact of traveling waves on sensory perception. The model predicts that spontaneous traveling waves will both increase and decrease the gain of a stimulus-evoked response, depending on wave phase. To test this, spontaneous waves will be recorded within MT and V1 as marmosets attempt to detect a faint visual stimulus. This will also allow researchers to test the model prediction that wave phase regulates perceptual sensitivity. Together, these analyses will help characterize the contributions of spontaneous traveling waves to cortical variability and perception, information critical for understanding brain disorders associated with failures in perception and attention, such as autism, schizophrenia, and Alzheimer?s disease.